Launching today

Koalr
Deploy risk scoring for every PR — before it merges
1 follower
Deploy risk scoring for every PR — before it merges
1 follower
Koalr scores every PR 0–100 for deploy risk using 36 signals — coverage delta, file expertise, change entropy, SLO burn rate, and more. Plus blast radius propagation, proactive AI briefings, autonomous reviewer, DORA metrics, and 23 integrations.
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Free Options
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Hey PH! Andrew here, founder of Koalr.
I built this after seeing the same pattern on every team I worked with: everyone knows which deploys are dangerous (large Friday PRs, first-time author in payments, no CODEOWNERS review) but nobody quantifies it ahead of time.
Koalr quantifies it. Every PR gets a 0–100 risk score before you merge. The model learns from your actual incident history — when a high-risk deploy causes an incident, that outcome feeds back and the model self-corrects to your team's patterns.
Three things I haven't seen any other engineering analytics platform do:
Blast Radius — model how a risky change propagates through your service dependency graph. You see every downstream service and its propagated risk, hop-by-hop, before you merge.
Proactive AI Briefings — Claude pushes a Slack digest every morning: high-risk open PRs, trending MTTR, incident patterns. Most dashboards gather dust. This interrupts.
Autonomous Reviewer — AI assigns reviewers by file-level expertise and comments on PRs with structured risk analysis. Zero config as a GitHub App.
Also: DORA metrics, CODEOWNERS governance, VS Code extension, iOS/Android apps, 23 integrations.
Free tier: 5 seats, no credit card. PH-exclusive: mention "ProductHunt" at signup for a 60-day trial.
Try the deploy risk calculator without an account: https://koalr.com/tools/deploy-r...
Happy to go deep on the methodology, blast radius algorithm, or anything else.